Detrimental Starfish Detection on Embedded System: A Case Study of YOLOv5 Deep Learning Algorithm and TensorFlow Lite framework
Abstract
There is a great range of spectacular coral reefs in the ocean world. Unfortunately, they are in jeopardy, due to an overabundance of one specific starfish called the coral-eating crown-of-thorns starfish (or COTS). This article provides research to deliver innovation in COTS control. Using a deep learning model based on the You Only Look Once version 5 (YOLOv5) deep learning algorithm on an embedded device for COTS detection. It aids professionals in optimizing their time, resources and enhancing efficiency for the preservation of coral reefs all around the world. As a result, the performance over the algorithm was outstanding with Precision: 0.93 - Recall: 0.77 - F1-score: 0.84.
Supporting Agencies
Keywords:
deep learning; computer vision; YOLO; embedded systemReferences
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